From 29b04098ef4c3d7822fb59478b94a6e03d5d2bc9 Mon Sep 17 00:00:00 2001 From: Ivan Pleshkov Date: Tue, 12 May 2026 03:05:35 +0200 Subject: [PATCH] rename deep dive article --- qdrant-landing/content/articles/turboquant-quantization.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/qdrant-landing/content/articles/turboquant-quantization.md b/qdrant-landing/content/articles/turboquant-quantization.md index 1a0a8d777..c2f4c2266 100644 --- a/qdrant-landing/content/articles/turboquant-quantization.md +++ b/qdrant-landing/content/articles/turboquant-quantization.md @@ -218,7 +218,7 @@ TurboQuant gives Qdrant a new path on the compression ladder: 8× compression at **Engineering deep-dives by the team that built this:** -* **[TurboQuant in Qdrant: tricks and ideas behind the implementation](https://turbo-quant-personal-site.pleshkov-ivan.workers.dev/blog/turboquant/)** — by Ivan Pleshkov. Every algorithmic extension explained: renormalization, the reversible LCG + Fisher-Yates Hadamard rotation, anisotropy compensation, P-Square calibration, support for L2 and unnormalized dot. The post walks through each idea against the companion [Python showcase](https://github.com/IvanPleshkov/turboquant-qdrant-showcase) — a readable toy-implementation to see exactly how each piece works in practice. +* **[TurboQuant + RaBitQ: a hybrid approach in Qdrant](https://turbo-quant-personal-site.pleshkov-ivan.workers.dev/blog/turboquant/)** — by [Ivan Pleshkov](https://www.linkedin.com/in/ivan-pleshkov/). Every algorithmic extension explained: renormalization, the reversible LCG + Fisher-Yates Hadamard rotation, anisotropy compensation, P-Square calibration, support for L2 and unnormalized dot. The post walks through each idea against the companion [Python showcase](https://github.com/IvanPleshkov/turboquant-qdrant-showcase) — a readable toy-implementation to see exactly how each piece works in practice. **Background:**